2.1 Literature Review
For many years in the construction industry, purely price-based contractor selection has been extensively used to obtain cheap prices and/or to avoid controversy. But choosing the cheapest offer often leads to problems including sub-standard quality, cost over- runs, delays and hence, false economics, as well as escalated claims and disputes etc. (Crowley and Hancher, 1995; El Wardani et al., 2006; Kumaraswamy, 2006; Palaneeswaran et al., 2007; Russell and Skibniewski, 1990). Also, as mentioned by Singh and Tiong (2006), “the construction industry has also witnessed the failure of contractors due to varying reasons such as financial problems, poor performance, or accidents arising from the lack of adequate safety consideration at work sites.” Cheng and Li (2004) confirmed that the performance of the project would be affected if the method for selecting the most appropriate contractors were not proper and reliable. Studies have shown that a “price-only” contractor selection system is inefficient in selecting the most capable contractors that have capacities to finish the project
successfully with a win-win result. Always choosing the lowest price tender may cause many problems, and final costs and durations may then turn out to be much more than those that may have resulted from choosing the 2nd (or 3rd) lowest bid. Other non-price evaluation criteria have been introduced into tender selection processes e.g.: financial stability, any failure to complete previous projects, experience, successfully completed projects, quality levels achieved, culture factors, financial strengths/ weaknesses, key personnel, organizational structure, management and technological resources (Holt et al., 1994; Kumaraswamy et al., 2007; Kumaraswamy, 1996; Russell et al., 1992; Russell and Skibniewski, 1988).
One of the important criteria that recurs in the above studies is past performance of the candidate contractors. The reason for past performance of contractors being important is because using a performance modelling process, we may predict the “multiple project performance outcomes for candidate contractors” (Alarcon and Mourgues, 2002). Furthermore, some contractor performance evaluation models have been developed and published by some researchers, like CQP evaluation model in pavement projects (Yasamis, 1999), QUALICON: Computer-Based System for CQM (Battikha, 2002), e- reporting system for contractor’s performance appraisal (Ng et al., 2002). Apart from theory, there are already some evaluation and information reporting systems used in practice by different agencies, like the Performance Assessment Scoring System (PASS) of the HK Housing Authority; Construction Quality Assessment System (CONQUAS) of the Building & Construction Authority, Singapore; both (a) the Contractor Performance Index System (CPIS), and the (b) Formula Approach & Marking Scheme Tender Evaluation Approach of the HK Works Branch of the HK Development Bureau; Counterparty Management Information System (COMIS) of the HK Housing Authority; Contractor Performance Assessment Reporting System (CPARS) of the US Naval Sea Logistics Centre Detachment Portsmouth; a website named ‘Contractor Power’ in U.K. providing contractors’ basic information, a website providing information on contracts by or on behalf of ‘Statistics Canada’. A comparison of the main Features of the above systems is shown in Table 1:
Table 1. Comparison of features between some existing systems
SYSTEM NAME REGION
Contractor Evaluation Information Storage Data available to: Project based Multi- criteria
PASS HK SAR Y Y HKHA^ Y Y
CONQUAS Singapore Y Y
Public/
Government Y Y
Contractor Performance
Index System HK SAR Y N HKWB# N Y
Formula Approach HK SAR Y* N HKWB# N Y
Marking Scheme HK SAR Y* N HKWB# N Y
COMIS HK SAR N Y HKHA^ N Y
CPARS U.S. Y Y U.S. Navy Y Y
Contractor Power U.K. N Y Public Y Y
Statistics Canada Canada N Y Public Y Y
*: for tender evaluation. ^: Hong Kong Housing Authority #: Hong Kong Works Branch
As seen from Table 1, Hong Kong has adopted a few different performance assessment, information collection, storage and evaluation systems. Among the systems used in Hong Kong, PASS is the one with the most features/functions. In this respect, it is also the most complex one. The system has been applied for almost 20 years, and accumulated a large volume of data on contractor performance assessment. Our case study was therefore carried out on this system.
2.2 Performance Assessment Scoring System (PASS)
The PASS system was introduced by the Hong Kong Housing Authority (HKHA) in 1990 to monitor its contractors in a more effective way. The main functions of the system are for work performance monitoring; for HKHA’s contractor list management (to maintain an up-dated list of ‘registered’ contractors); as well as for applying in the tender process, both for selection of tenderers and also to inform tender assessment. The main skeleton of the system is as follows:
SW - Structural Works Assessment
AWI - Architectural Works (Interim) Assessment AWF - Architectural Works (Final) Assessment SA - Safety Assessment
SA1 - score for Safety & Health Management System SA2 - score for Implementation of the Safety & Health Plan SA3 - General Site Safety
SA4 - Block Related Safety
PA - Programme and Progress Assessment PA1 - Programming
PA2 - Milestone Dates (Building Service) PA3 - Milestone Dates (Prior to Completion) PA4 - Milestone Dates (Structural Works) PA5 - Milestone Dates (Architecture Works)
OOE - Environmental and Other Obligations Assessment OOE1 - Environmental, Health and Other Provisions OOE2 - Site Security, Access and Storage of Materials IA - Management Input Assessment
IA2 - Resources
IA3 - Co-ordination and Control IA4 - Documentation
MPA - Maintenance Period Assessment MPA1 - Outstanding Works
MPA2 - Defects and Works of Repair
MPA3 – Management, Co-ordination and Documentation
We can see from the PASS structure that, assessment criteria a, b and c are more about the output assessment, which assess the quality of the final product, either from the structural side or from the architectural side. These three assessment criteria contribute to 70% of the final project score during the construction period. On the contrary, assessment criteria d - g are more concerned with assessing general issues, with more emphasis on project process control. The results in these ‘sections’ can reflect the effort the contractor has put into the project in some degree and can also reflect the influence that ‘input factors’ have had on the project. These four sections contribute to 30% of the final project score during the construction period. Assessment criterion h is to assess the contractor’s performance during the maintenance period, which is normally 24 months. Most of the assessments are done on a quarterly base. PASS adopts a 4 quarter rolling measurement, which means the scores in the past 4 quarters will be used to generate the project score. Then the arithmetic average of the projects scores for all the projects done by the contractor in the preceding 4 quarters will be calculated as the contractor score. This contractor score will be used in the tender opportunity allocation process and tender selection process in the current quarter.
The reported case study focuses on testing whether a better performance in the General Assessment will influence a contractor’s performance in the Output Assessment or not, and furthermore to identify the factors that can be used for predicting performance. Indeed, once any relationship between the input factors and output factors has been identified, then we may use these factors for predicting performance. In short, it is hypothesised that better performance against criteria d to g (which can be taken as ‘input’ factors) can help generate a better quality of the final product of the project (‘output’ criteria/ factors a to c).